University of Manitoba Asper School of Business 3500 DBMS Bob Travica Chapter 3 Data Normalization Based on G. Post, DBMS: Designing & Building Business Applications Updated 2010

Practically boils down to defining tables so that Normalization The process of putting data into the format of relational databases (or, organizing data for relational databases) Practically boils down to defining tables so that a) problems (anomalies) with insertion, deletion and modification of data are avoided b) data quality is preserved (completeness, integrity) c) redundancy is reduced

Relational Database Terminology Relational database: A collection of tables (relations). Tables store atomic data. Table: A collection of columns (attributes, properties, fields) describing an entity (class). Table is also a collection of rows (records) each with the same number of columns. Each row stores data on objects (entity instances). EmployeeID TaxpayerID LastName FirstName HomePhone Address 12512 888-22-5552 Cartom Abdul (603) 323-9893 252 South Street 15293 222-55-3737 Venetiaan Roland (804) 888-6667 937 Paramaribo Ln 22343 293-87-4343 Johnson John (703) 222-9384 234 Main Street 29387 837-36-2933 Stenheim Susan (410) 330-9837 8934 W. Maple Attributes/ Properties Rows/Objects Entity (Class): Employee Table: Employee

Relational Database Terminology – Primary Key Every table has a primary key (key) – an attribute that uniquely identifies each row (e.g., EmployeeID on previous slide) Primary key can span more than one column combined (combined, composite, concatenated) key. OrderItem OrderID ItemID Quantity 1 229 2 1 253 4 2 229 1 2 555 4 Other attributes are called non-key columns. Primary key can be generated automatically by DBMS – surrogate key. Note: Watch for data types (e.g., number vs. text) and naming rules (arbitrary but consistent).

Relational Database Shorthand Notation Primary key is underlined Non-key columns Table name Customer(CustomerID, LastName, FirstName, Address, City, State, ZipPostalCode, TelephoneNumber) * Note: Telephone number can be used as a “backup key.”

Order Management Application Non-Normalized Class Diagram Customer Order Salesperson Item OrderItem 1 * Normalized Tables Diagram, Schema Customer Order Salesperson Item 1 * OrderItem Association class (ItemOrdered, OrderDetail, etc.)

Shorthand Notation for Normalized Tables Diagram – Foreign Key Customer(CustomerID, Name, Address, City, Phone) Salesperson(EmployeeID, Name, DateHired) Order(OrderID, OrderDate, CustomerID, EmployeeID) OrderItem(OrderID, ItemID, Quantity) Item(ItemID, Description, ListPrice) Foreign Key = Attribute that is a key in another table (e.g., CustomerID in Order). Logic & naming of OrderItem: Replacing the Order-Item many-to-many relationship with two 1:M relationships. OrderItem has a combined key—OrderID+ItemID.

NORMALIZATION

“Dynamic Data” (Transaction Data) — Operations Entities Video Store Transaction Management System (VTMS): Classes, Columns & Business Rules “Dynamic Data” (Transaction Data) — Operations Entities (change more often) “Static (Master) Data”— Market &Inventory Entities (don’t change often) Customer table Key: CustomerID Attributes: Name Address Phone Video table Key: VideoID Attributes : Title RentalFee Rating… RentalTransaction table Key: TransactionID Attributes : CustomerID Date VideoRented table Key: TransactionID + VideoID Attributes: Copy# Business Rules: A customer can have many transactions… Each transaction can include many videos… A transaction can include only one copy of a particular video...

Normalized Schema for STMS In Short Hand Notation Customer(CustomerID, LastName, FirstName, Address, City, …) Transaction data stored in 2 tables due to the business rule that a rental transaction can include just 1 copy of a video. RentalTransaction(TransID, RentDate, CustomerID) VideoRented(TransID, VideoID, Copy#) Video(VideoID, Title, RentalFee)

Why Normalize – Avoiding data anomalies How to get to those four tables from the business rule? Are not these two tables enough? Customer Video * rents * Partial schema for this class diagram: Customer(CustomerID, LastName, FirstName, … VideoID, Date) Video(VideoID, Title, RentalFee) Not good because: Transaction data would have to be part of table Customer (or Video), which causes repetition of Customer data for each transaction—redundancy. Deletion of transaction data causes deletion of customer data— deletion anomaly. New customers cannot be added because VideoID as part of the key in Video cannot be empty —insertion anomaly.

Normalization Customer Video * rents * RentalTransaction 1 * has Rule of Thumb: Each many-to-many relationship must be replaced by 2 one-to-many relationships (see Customer-Order-Item above). Customer Video * rents * RentalTransaction 1 * has includes 1. How to track different copies of same video? Still M:M Customer Video RentalTransaction 1 * has contains VideoRented 1 includes* is rented 2. Table VideoRented tracks each copy of a particular video. Multiplicity on the video side is forced down to 1, which enforces the business rule that only 1 copy of a video can be rented out in a transaction (slides 9 & 10).

Normalization – Step by Step RentalForm(TransID, RentDate, (CustomerID, Name, Address, City, State, …), (VideoID, Copy#, Title, RentalFee)) Interview users, understand output needed. Put data into a large table (RentalForm). Pick out attributes. Find repeating groups. Look for potential keys. Identify computed values.

Problems with Repeating Groups (Sections) RentalForm(TransID, RentDate, (CustomerID, Phone, Name, Address, City, State, …), (VideoID, Copy#, Title, Rent)) Repeating Groups TransID RentDate CustomerID LastName Phone Address VideoID Copy# Title Rent 1 4/18/02 3 Washington 502-777-7575 95 Easy Street 1 2 2001: A Space Odyssey $1.50 1 4/18/02 3 Washington 502-777-7575 95 Easy Street 6 3 Clockwork Orange $1.50 2 4/30/02 7 Lasater 615-888-4474 67 S. Ray Drive 8 1 Hopscotch $1.50 2 4/30/02 7 Lasater 615-888-4474 67 S. Ray Drive 2 1 Apocalypse Now $2.00 2 4/30/02 7 Lasater 615-888-4474 67 S. Ray Drive 6 1 Clockwork Orange $1.50 Problems: Insertion Anomaly: Inserting a Customer creates blank space in video and transactions columns. With VideoID as part of key, customer and video data must be inserted at the same time. Deletion Anomaly: Delete transaction data => delete customer and video data. Useless redundancy & wasted storage. If there are repeating sections, the table is not in the first normal form (1NF).

First Normal Form (1NF) 1NF: A table is in 1NF if it does not have repeating sections. Normalization Procedure: Remove repeating sections by splitting the initial table into new tables. Link new tables on the key from the initial table. RentalTransaction(TransID, RentDate) Video(TransID, VideoID, Copy#, Title, RentalFee) Customer(TransID, CustomerID, Phone, Name, Address, City, State, ZipCod) New Reminder of initial table

Problems with First Normal Form Apply only to tables with concatenated keys: TransID VideoID Copy# Title RentalFee 1 1 2 2001: A Space Odyssey $1.50 1 6 3 Clockwork Orange $1.50 2 8 1 Hopscotch $1.50 2 2 1 Apocalypse Now $2.00 2 6 1 Clockwork Orange $1.50 Video There are problems concerning the relationship between the key and non-keys. Concept of Functional Dependence: An attribute depends on another attribute if changing the later causes a change of the former. The key column must be sufficient for determining values of the non-key columns.

Problems with First Normal Form (cont.) Copy# depends on full key (TransID + VideoID) -- Full Functional Dependency on the key. Combined determine Video(TransID, VideoID, Copy#, Title, RentalFee) Sufficient to determine VideoID is sufficient for predicting titles and rental fees. There is Partial Functional Dependency between the combined key and Title and RentalFee. If any non-key column depends just on a part of the key (there is partial functional dependence), the table is not in 2NF.

Second Normal Form (2NF) 2NF: A table is in 2NF if it is (a) is 1NF and (b) non-key columns depend on the entire key. Normalization Procedure: Move TransID and Copy# into a new table VideoRented. Preserve a link between Video and VideoRented by importing VideoID in table VideoRented. Video(TransID, VideoID, Copy#, Title, RentalFee) move export VideoRented(TransID, VideoID, Copy#) New Video(VideoID, Title, RentalFee) Resulting Video table

Finalize 2NF… Table Customer must also be brought into 2NF by moving TransID into table RentalTransaction (already there) and exporting CustomerID. Customer(TransID, CustomerID, Phone, Name, Address, City, State,…) RentalTransaction(TransID, RentDate, CustomerID) move export Completed Resulting Customer table Customer(CustomerID, LastName, FirstName, Address, City, …)

Third Normal Form (3NF) Problems with 3NF: If any non-key depends on some other non-key there is transitive dependency and the table is not in 3NF. 3 NF: Table is in 3NF if it is (a) in 2NF, and (b) each non-key attribute depends on the key only. Our design is already in 3NF! Customer(CustomerID, LastName, FirstName, Address, City, …) VideoRented(TransID, VideoID, Copy#) Video(VideoID, Title, RentalFee) RentalTransaction(TransID, RentDate, CustomerID)

3NF Example Table in 2NF: Sales(CustomerID, CustomerName, Salesperson, Region) Violation of 3NF: Region (non-key) is dependent on Salesperson. Solution – split table into 12 tables: : Sales(CustomerID, CustomerName, Salesperson) Salesperson(Salesperson, Region) Forms beyond the 3rd are very rare and reaching 3NF is sufficient for practical purposes.

Schema for VSTMS Allowing Multiple Copies per Transaction Customer(CustomerID, LastName, FirstName, Address, City, …) Video(VideoID, Title, RentalFee) RentalTransaction(TransID, CustomerID, VideoID, RentDate) 1 * * 1 Note: Video key can be made unique: VideoID = 85.1 (decimal place designates a copy), or 85c1 (text type), or use a bar code for each video and copy (ItemID).

Normalization Summary (Must know!) 1) If a table has repeating sections, there is huge redundancy and different classes are mixed together. Split the table, so that classes are clearly differentiated. Result: 1NF. 1NF: A table is in 1NF if it does not have repeating sections. 2) If a table has a combined key, non-key columns may depend on just a part of the primary key, and so there is partial functional dependency. Split the table so that in new tables non-keys depend on the entire key. Result: 2NF. 2NF: A table is in 2NF if it is in 1NF and non-key columns depend on the entire key. 3) If a non-key depends on another non-key, there is transitive dependency. Split the table so that in new tables each non-key depends on the key and nothing but the key. Result: 3NF. 3NF: A table is in 3NF if it is in 2NF and all non-keys depend on the key only.